The present invention relates to Information Handling System (IHS), in general, and in particular to determining the power consumption of a software product running on an IHS.
Power consumption has become a major issue for Government and commercial enterprises as a significant added cost in the activities of the enterprises. Computer software, running on an IHS, is one of the many activities contributing to the overall energy consumption. Even though the contribution of a single program may be miniscule when the total power consumption is taken into consideration, there are a large number of software products running on all types of IHS, and the aggregate power consumption of these products can be relatively high. In order to determine the effect of software products on total energy consumption, a technique, and a mechanism are required to make an accurate, and a reliable projection on the power consumption of the software products.
Commercial enterprises are generally concerned with the energy consumption of software application products that will be run on future IHS, that they may be planning to purchase. Oftentimes, a buyer of a future IHS may ask the vendor to provide a power projection analysis for a particular software product. The particular software product may be that of the buyer or that of a third party. This request puts pressure on the vendor to make sure the information that is given to the buyer is accurate and reliable. This is particularly important if the power consumption projection is inserted in the sales agreement. If the product fails to meet the terms of the power consumption projection, the vendor could be liable for whatever loss the buyer suffers as a result of the product failing to perform according to the power projection analysis. The loss to the vendor could be very high, especially on very expensive IHS products. To minimize the potential exposure, the vendor may provide a very conservative power projection estimate or an estimate that includes a lot of conditions. Oftentimes, the buyer wants straight-forward estimates, and an estimate that is too conservative and/or contains too many contingencies could result in loss of business to the vendor.
Another likely scenario occurs when a customer has limited power in its data center. In this case, the power projection must determine the number of nodes that a customer can use. If the power estimate is over estimated, the size of the system will be smaller since the estimated power use per node is too high, in comparison to what it could have been had the power per node estimate been correct, resulting in lower application performance. On the other hand, if the power projection estimate is under estimated the customer may not be able to power all the nodes. In either case the customer could be unhappy which is not good for business.
Estimating power consumption of an application program on future system can be complex, time consuming, and sometimes impossible. Many hurdles have to be overcome in order to set up and extract meaningful information on the projected power consumption of the application program. In the past, projections have been based on general estimates, ad hoc determination, and intuition from experience but these techniques can lead to large errors in system cost estimates. Another approach uses aggregate power measurements over many benchmarks but this technique could encompass an error range in excess of 50%, in projection for an individual application. Still another approach uses detailed analysis of application characteristics projecting to future systems but this is a tedious time consuming process that often does not yield good results. In yet another approach estimates are based upon company's literature or academic papers which are often inaccurate.